Friday links: everything old is new again, and more

Also this week: how to become really highly cited, robot statistician, universities vs. brands, and more.

From Jeremy:

We’re a bit late to this: the 100 most cited scientific papers ever. See how many you can guess before clicking through. Hint: They’re mostly methods papers. Hint #2: There are no ecology papers (not even close!). A few papers on statistical methods and software packages for phylogenetic estimation are the only evolution papers that make the cut. Of course, really influential work is rarely cited, as it’s just part of the background knowledge every scientist is supposed to have. If that weren’t the case, R. A. Fisher would probably be the most-cited scientist ever.

Speaking of citations: according to this preprint, a (modestly) greater fraction of citations now go to papers >10 (or 15, or 20) years old than was the case in 1990. Most areas of scholarship show the trend, albeit to varying degrees. The study’s based on Google Scholar data; I’m not sure if that creates any artifacts. (ht Marginal Revolution)

How to spot the holes in a data-based news story. Very good reading for undergrad stats classes. Based on compelling real world examples. Particularly good on driving home the points that correlation is not causation, and the reasons why statistically controlling for confounding variables often is ineffective.

Universities are not brands.

Good tips for giving a good talk. Includes some advice I haven’t seen elsewhere.

Jeremy Yoder has an interview with the founders of Haldane’s Sieve, a website that promotes and discusses preprints in population and evolutionary genetics. Always interesting to hear from folks who are experimenting with new ways of doing things. Glad to see that they recognize a key virtue of the current pre-publication peer review system: it ensures that at least some close attention is paid to every paper. I’m pessimistic that there’s any way to prevent serious attention concentration post-publication (see also here). Indeed, isn’t Haldane’s Sieve itself a mechanism for concentrating post-publication attention?  I was also interested in their perception that the scientific publication system is mostly an overly-critical, “down-voting” system. That might be true of pre-publication review, but if anything I think the opposite is the case post-publication. Post-publication, bandwagons and zombie ideas far outnumber Buddy Holly ideas, and even clear-cut mistakes continue to attract attention and citations much longer than they should. So if you want a scientific publication system that achieves some ideal balance of “up voting” enthusiasm and “down voting” criticism, well, maybe our current system isn’t too far off the mark? Our current pre-publication review system also has the advantage that it is a system, with agreed, enforced rules and norms that at least in principle (and I think for the most part in practice) apply equally to everybody, and that everybody knows they’re signing up for when they start doing science (see here for discussion). The next person who figures out what the rules and norms of post-publication commenting should be (in particular, what the rules and norms for critical comments should be), gets everyone to agree to them, and figures out how to enforce them, will be the first.

A while back I discussed the suggestion for a “deterministic statistical machine”–basically, statistical software that would automatically choose an appropriate analysis and then do it for you. It would be aimed at users who don’t know statistics, much as premade meals are aimed at people who can’t (or won’t) cook. Now someone’s invented such a machine.

What to do if you’ve been denied tenure, or are about to be. Related: Meg’s old post on how to navigate the tenure track and maximize the odds that you never need to click that link (although once you have a tenure-track faculty position, the odds are very much in your favor).

Literary Starbucks.🙂

And finally: a bear misunderstands the Wildlife Photographer of the Year competition.🙂

4 thoughts on “Friday links: everything old is new again, and more

  1. It turns out the difference between the number of citations listed on Google Scholar (GS) and Web of Science (WOS) is huge! Two of the papers I erroneously thought would be on this list (based on GS) are Watts & Strogatz (1998) Collective dynamics of ‘small-world’ networks. Nature 393, 440-442 [24064 citations GS; 10642 citations WOS] and Barabási & Albert (1999) Emergence of scaling in random networks. Science 286, 509-512 [21033 GS; 10267 WOS]. My consolation is that they are fairly new papers, still increasing their annual citation rate; they’ll probably crack the top 100 within a few years. Both of them are about midway down that list, if ordered by number of citations per year rather than absolute number.

    • Yes, Google Scholar indexes all sorts of crap. It lists me as having “publications” that are just the entries for my papers in the journal TOCs. It credits me with numerous “publications” and “citations” that are just ESA meeting abstracts (or citations in same). You can of course wave your arms about how giving a talk or being cited in a talk or etc. represents “influence” in some broad sense. But personally, I prefer not to lump together apples and oranges. So if I ever want to know how often I or someone else has been published or cited in the usual senses of “published” and “cited”, I look at WoS.

  2. most popular links so far (all very close): speaking tips, the silly bear picture, and universities are not brands. I figured the first two would be the top two, surprised that the third is right up there.

  3. I agree and disagree with the link about branding. Universities are inescapably brands. You can object to the use of a business word and call it reputation or something else if you like, but the fact that people have gestalt impressions of institutions that is part based on fact and part based on more emotive responsive and which can be managed is undeniable. Individual researchers have brands too (Jeremy’s brand is probably something like theoretical community ecology meets microcosms with a heavy dose of dynamic ecology and zombie ideas – my brand is probably something like big data macroecology, frequent skeptic, and – I like to think – writes unusually clear papers).

    But I do agree with the piece that universities have gotten too cynical and frankly stupid about trying to manage their brand. What the examples in the link highlight are very misguided attempts at brand.- or at best attempts at quick-fix ways to achieve brand which is an oxymoron. Having your own domain, a standardized background on websites (a big push at my university right now), hiring brand managers who write stupid articles that look terrible in an academic context, etc at best don’t work.

    The key to a good brand is to have some areas of excellence and to continue maintain those areas of excellence over the long haul and to be able to verbalize those areas of excellence and to repeat that same message over a long period of time. Brand is primarily about discipline (sticking to the same strengths long enough that people paying only partial attention begin to make the association) and focus (you can’t have a brand that says you do everything well).

    What the examples in the link highlight are very misguided attempts at brand.- or at best attempts at quick-fix ways to achieve brand which is an oxymoron. Having your own domain, a standardized background on websites (a big push at my university right now), hiring brand managers who write stupid articles that look terrible in an academic context, etc at best don’t work.

    By the way any academic who wants to think about managing their own brand or the brand of say a research center they are part of should give a read to “The 22 immutable laws of marketing” by Reis and Trout ( This is an all time business classic, avery quick entertaining read (<1 hour), fascinating insight into the good and branding moves of big companies you will recognize, and fundamentally changed the way I think about reputation (and very much grounded in the idea of brand as discipline and focus – not quick superficial fixes)

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